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Introduction to Data Analytics and Artificial IntelligenceLaajuus (3 cr)

Code: TTC2050

Credits

3 op

Teaching language

  • Finnish
  • English

Responsible person

  • Antti Häkkinen
  • Juha Peltomäki

Objective

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Qualifications

Ohjelmoinnin perusteet

Assessment criteria, satisfactory (1)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Assessment criteria, good (3)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Assessment criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Timing

13.01.2025 - 09.02.2025

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Teaching languages
  • English
  • Finnish
Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • ZJA25KTIDA1
    Avoin amk, Data-analytiikka 1, Verkko
  • ZJA25KTI
    Avoin AMK, tekniikka, ICT

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online

Learning materials and recommended literature

Course website (lecture material, exercises, recorded lecture videos)

Teaching methods

Distance learning (exercises, familiarization with lecture material, recorded videos of practical examples)

Student workload

Getting to know the online lecture material 35 hours (recorded lectures with teacher-led exercises)
Distance learning 46 hours (exercises)
A total of 81 hours

Further information for students

The evaluation of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 31.03.2025

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

0 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV23S2
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Weekly guidance for doing exercises in classrooom

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)

Student workload

Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 31.03.2025

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

0 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV23S3
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Weekly guidance for doing exercises in classrooom

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)

Student workload

Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 31.03.2025

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

0 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV23S5
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Weekly guidance for doing exercises in classrooom

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)

Student workload

Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 31.03.2025

Number of ECTS credits allocated

3 op

Virtual portion

3 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

0 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV23SM
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online sessions

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

- Several online sessions during the implementation (the student can join the online session and get support from the teacher in doing the exercises)
- Distance learning (students can complete the course at their own pace, doing exercises independently)

Student workload

Distance learning 71h (exercises)
Online guidance sessions 10h
A total of 81 hours

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 31.03.2025

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • English
Seats

0 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TIC23S1
    Bachelor's Degree Programme in Information and Communications Technology

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Weekly guidance for doing exercises in classrooom

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)

Student workload

Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

18.11.2024 - 09.01.2025

Timing

13.01.2025 - 31.03.2025

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

0 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV23S1
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Weekly guidance for doing exercises in classrooom

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)

Student workload

Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Timing

26.08.2024 - 29.09.2024

Number of ECTS credits allocated

3 op

Virtual portion

3 op

Mode of delivery

Online learning

Unit

School of Technology

Teaching languages
  • Finnish
Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • ZJA24STI
    Avoin AMK, tekniikka, ICT
  • ZJA24STIDA1
    Avoin amk, Data-analytiikka 1, Verkko

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Verkossa

Learning materials and recommended literature

Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)

Teaching methods

Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)

Student workload

Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h

Further information for students

Opintojakson arviointi muodostuu palautetuista harjoituksista.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Timing

09.01.2024 - 11.02.2024

Number of ECTS credits allocated

3 op

Virtual portion

3 op

Mode of delivery

Online learning

Unit

School of Technology

Teaching languages
  • English
Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • ZJA24KTIDA1
    Avoin amk, Data-analytiikka 1, Verkko

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Verkossa

Learning materials and recommended literature

Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)

Teaching methods

Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)

Student workload

Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h

Further information for students

Opintojakson arviointi muodostuu palautetuista harjoituksista.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

20 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV22S1
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online lectures and, in addition, guidance in doing exercises in class

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises

Student workload

Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

20 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV22S2
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online lectures and, in addition, guidance in doing exercises in class

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises

Student workload

Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

20 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV22S3
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online lectures and, in addition, guidance in doing exercises in class

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises

Student workload

Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

20 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV22S4
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online lectures and, in addition, guidance in doing exercises in class

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises

Student workload

Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

20 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV22S5
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online lectures and, in addition, guidance in doing exercises in class

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises

Student workload

Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

20 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV22SM
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online lectures and, in addition, guidance in doing exercises in class

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises

Student workload

Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

20 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV22SM2
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online lectures and, in addition, guidance in doing exercises in class

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises

Student workload

Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

20.11.2023 - 04.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • English
Seats

20 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TIC22S1
    Bachelor's Degree Programme in Information and Communications Technology

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Lectures and, in addition, guidance in doing exercises in class

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises

Student workload

Lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Timing

28.08.2023 - 01.10.2023

Number of ECTS credits allocated

3 op

Virtual portion

3 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • ZJA23STI
    Avoin AMK, tekniikka, ICT
  • ZJA23STIDA1
    Avoin amk, Data-analytiikka 1, Verkko

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Verkossa

Learning materials and recommended literature

Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)

Teaching methods

Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)

Student workload

Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h

Further information for students

Opintojakson arviointi muodostuu palautetuista harjoituksista.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Timing

09.01.2023 - 19.02.2023

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Teaching languages
  • Finnish
Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • ZJA23KTIDA1
    Avoin amk, Data-analytiikka 1, Verkko

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Verkossa

Learning materials and recommended literature

Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)

Teaching methods

Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)

Student workload

Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h

Further information for students

Opintojakson arviointi muodostuu palautetuista harjoituksista.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

01.11.2022 - 05.01.2023

Timing

09.01.2023 - 28.04.2023

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • English
Seats

0 - 35

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TIC21S1
    Bachelor's Degree Programme in Information and Communications Technology

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)

Student workload

Lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

01.11.2022 - 05.01.2023

Timing

09.01.2023 - 28.04.2023

Number of ECTS credits allocated

3 op

Virtual portion

3 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

0 - 210

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV21S3
    Tieto- ja viestintätekniikka (AMK)
  • TTV21S5
    Tieto- ja viestintätekniikka (AMK)
  • TTV21SM
    Tieto- ja viestintätekniikka (AMK)
  • TTV21S2
    Tieto- ja viestintätekniikka (AMK)
  • TTV21S1
    Tieto- ja viestintätekniikka (AMK)

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Online

Learning materials and recommended literature

Course material page (lecture materials, exercises)

Teaching methods

Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)

Student workload

Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Total 81h

Further information for students

The assessment of the course consists of returned exercises.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

01.08.2022 - 25.08.2022

Timing

29.08.2022 - 02.10.2022

Number of ECTS credits allocated

3 op

Mode of delivery

Face-to-face

Unit

School of Technology

Teaching languages
  • Finnish
Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • ZJA22STIDA1
    Avoin amk, Data-analytiikka 1, Verkko

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Verkossa

Learning materials and recommended literature

Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)

Teaching methods

Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)

Student workload

Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h

Further information for students

Opintojakson arviointi muodostuu palautetuista harjoituksista.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet

Enrollment

16.12.2021 - 09.01.2022

Timing

14.02.2022 - 31.03.2022

Number of ECTS credits allocated

3 op

Virtual portion

3 op

Mode of delivery

Online learning

Unit

School of Technology

Campus

Lutakko Campus

Teaching languages
  • Finnish
Seats

0 - 30

Degree programmes
  • Bachelor's Degree Programme in Information and Communications Technology
  • Bachelor's Degree Programme in Information and Communications Technology
Teachers
  • Antti Häkkinen
Groups
  • TTV19SM
    Tieto- ja viestintätekniikka
  • TTV19S1
    Tieto- ja viestintätekniikka
  • TTV20SM
    Tieto- ja viestintätekniikka
  • TTV19S3
    Tieto- ja viestintätekniikka
  • TTV19S2
    Tieto- ja viestintätekniikka
  • TTV19S5
    Tieto- ja viestintätekniikka
  • ZJA22KTIDA1
    Avoin AMK, tekniikka, ICT, Data-analytiikka1

Objectives

Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.

EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice

Content

Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas

Time and location

Verkossa

Learning materials and recommended literature

Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)

Teaching methods

Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)

Student workload

Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h

Further information for students

Opintojakson arviointi muodostuu palautetuista harjoituksista.

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.

Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.

Evaluation criteria, good (3-4)

Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.

Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.

Evaluation criteria, excellent (5)

Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.

Prerequisites

Ohjelmoinnin perusteet